Large-scale genome-wide association study of coronary artery disease in genetically diverse populations
暂无分享,去创建一个
Yan V. Sun | T. Assimes | Hua Tang | Y. Kamatani | H. Leonard | D. Rader | C. Haiman | L. Le Marchand | B. Voight | S. Kathiresan | L. Wilkens | M. Ritchie | I. Kullo | S. Buyske | K. North | R. Do | P. Natarajan | D. Saleheen | J. Bis | J. Gaziano | S. Damrauer | C. Kooperberg | G. Jarvik | R. Loos | S. Hebbring | A. Bick | V. Napolioni | S. L. Clarke | J. Haessler | Yingchang Lu | M. Graff | A. Giri | L. Lange | T. Maddox | B. Namjou | N. Sinnott-Armstrong | Huaying Fang | K. Kaufman | P. Reaven | S. Verma | Kaoru Ito | Y. Ho | S. Raghavan | Kelly Cho | Stephen W. Waldo | Xiang Zhu | K. Ishigaki | A. Gordon | G. Wojcik | J. Huffman | I. Stanaway | D. Klarin | O. Dikilitas | M. Levin | C. Tcheandjieu | J. Lynch | Kyong‐Mi Chang | R. Kember | C. Avery | K. Lee | M. Vujkovic | Jennifer S. Lee | A. Baras | S. Pyarajan | J. Gaziano | A. Hilliard | M. Plomondon | Shining Ma | B. Gorman | L. Lotta | Rebecca J Song | N. Tsao | K. Chaudhary | P. Tsao | Elizabeth R. Hauser | Jie Huang | Peter W F Wilson | Christopher J. O’Donnell | S. Koyama | M. Verbanck | Fei Chen | Botong Shen | Donald R Miller | P. Wilson | C. O’Donnell | Nasa Sinnott-Armstrong | S. Clarke | E. Hauser | K. Ito | Yan V. Sun | R. Loos | Ayush Giri | K. Ito | J. Lynch | Ozan Dikilitas | M. Vujković
[1] Andrew D. Johnson,et al. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data , 2022, Nature Genetics.
[2] Christopher D. Brown,et al. The power of genetic diversity in genome-wide association studies of lipids , 2021, Nature.
[3] Ryan W. Kim,et al. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices , 2021, Nature Communications.
[4] Yan V. Sun,et al. Genome-wide analysis identifies novel susceptibility loci for myocardial infarction. , 2021, European heart journal.
[5] Sathish Kumar Jayapal,et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019 , 2020, Journal of the American College of Cardiology.
[6] H. Aburatani,et al. Population-specific and trans-ancestry genome-wide analyses identify distinct and shared genetic risk loci for coronary artery disease , 2020, Nature Genetics.
[7] M. Kanai,et al. Large-scale genome-wide association study in a Japanese population identifies novel susceptibility loci across different diseases , 2020, Nature Genetics.
[8] Marc S. Williams,et al. Predictive Utility of Polygenic Risk Scores for Coronary Heart Disease in Three Major Racial and Ethnic Groups. , 2020, American journal of human genetics.
[9] Alexander E. Lopez,et al. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ethnic meta-analysis , 2020, Nature Genetics.
[10] Grant D. Huang,et al. Genotyping Array Design and Data Quality Control in the Million Veteran Program. , 2020, American journal of human genetics.
[11] Man-Li Zhang,et al. Oncogenic functions of the EMT-related transcription factor ZEB1 in breast cancer , 2020, Journal of Translational Medicine.
[12] P. Tso,et al. Regulation of intestinal lipid metabolism: current concepts and relevance to disease , 2020, Nature Reviews Gastroenterology & Hepatology.
[13] Lisa Bastarache,et al. Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation , 2019, JMIR Medical Informatics.
[14] Julie A. Lynch,et al. Harmonizing Genetic Ancestry and Self-identified Race/Ethnicity in Genome-wide Association Studies. , 2019, American journal of human genetics.
[15] B. Baradaran,et al. The crucial role of ZEB2: From development to epithelial‐to‐mesenchymal transition and cancer complexity , 2019, Journal of cellular physiology.
[16] Shing Wan Choi,et al. PRSice-2: Polygenic Risk Score software for biobank-scale data , 2019, GigaScience.
[17] Clint L. Miller,et al. Atheroprotective roles of smooth muscle cell phenotypic modulation and the TCF21 disease gene as revealed by single-cell analysis , 2019, Nature Medicine.
[18] Alicia R. Martin,et al. Clinical use of current polygenic risk scores may exacerbate health disparities , 2019, Nature Genetics.
[19] Dajiang J. Liu,et al. Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci , 2019, Molecular Psychiatry.
[20] Helen E. Parkinson,et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019 , 2018, Nucleic Acids Res..
[21] Matthew Stephens,et al. Large-scale genome-wide enrichment analyses identify new trait-associated genes and pathways across 31 human phenotypes , 2018, Nature Communications.
[22] Shu Ye,et al. Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults , 2018, Journal of the American College of Cardiology.
[23] Christian Gieger,et al. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits , 2018, Nature Genetics.
[24] T. Heskes,et al. Conditional and interaction gene-set analysis reveals novel functional pathways for blood pressure , 2018, Nature Communications.
[25] Luke R. Lloyd-Jones,et al. Genome-wide association analyses identify 143 risk variants and putative regulatory mechanisms for type 2 diabetes , 2018, Nature Communications.
[26] Mary E. Haas,et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations , 2018, Nature Genetics.
[27] K. Reue,et al. Sex differences in obesity, lipid metabolism, and inflammation—A role for the sex chromosomes? , 2018, Molecular metabolism.
[28] D. Whiteman,et al. Height and overall cancer risk and mortality: evidence from a Mendelian randomisation study on 310,000 UK Biobank participants , 2018, British Journal of Cancer.
[29] P. Visscher,et al. Meta-analysis of genome-wide association studies for height and body mass index in ∼700,000 individuals of European ancestry , 2018, bioRxiv.
[30] Erdogan Taskesen,et al. Functional mapping and annotation of genetic associations with FUMA , 2017, Nature Communications.
[31] Raquel S. Sevilla,et al. Exome-wide association study of plasma lipids in >300,000 individuals , 2017, Nature Genetics.
[32] Mary Goldman,et al. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics , 2016, Nature Communications.
[33] R. Mägi,et al. Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution , 2017, Human molecular genetics.
[34] Rasool Tahmasbi,et al. Comparison of methods that use whole genome data to estimate the heritability and genetic architecture of complex traits , 2017, Nature Genetics.
[35] He Zhang,et al. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease , 2017, Journal of the American College of Cardiology.
[36] Themistocles L Assimes,et al. Genetics: Implications for Prevention and Management of Coronary Artery Disease. , 2016, Journal of the American College of Cardiology.
[37] S. Fullerton,et al. Genomics is failing on diversity , 2016, Nature.
[38] R. Collins,et al. No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis , 2016, Scientific Reports.
[39] Alan M. Kwong,et al. Next-generation genotype imputation service and methods , 2016, Nature Genetics.
[40] Shane A. McCarthy,et al. Reference-based phasing using the Haplotype Reference Consortium panel , 2016, Nature Genetics.
[41] Mary Brophy,et al. Million Veteran Program: A mega-biobank to study genetic influences on health and disease. , 2016, Journal of clinical epidemiology.
[42] Gabor T. Marth,et al. A global reference for human genetic variation , 2015, Nature.
[43] J. Danesh,et al. A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease , 2016 .
[44] P. Visscher,et al. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index , 2015, Nature Genetics.
[45] A. Reiner,et al. Leveraging Multi-ethnic Evidence for Mapping Complex Traits in Minority Populations: An Empirical Bayes Approach. , 2015, American journal of human genetics.
[46] Ira Tabas,et al. Recent insights into the cellular biology of atherosclerosis , 2015, The Journal of cell biology.
[47] Joris M. Mooij,et al. MAGMA: Generalized Gene-Set Analysis of GWAS Data , 2015, PLoS Comput. Biol..
[48] J. Hirschhorn,et al. Biological interpretation of genome-wide association studies using predicted gene functions , 2015, Nature Communications.
[49] Tamara S. Roman,et al. New genetic loci link adipose and insulin biology to body fat distribution , 2014, Nature.
[50] M. Daly,et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies , 2014, Nature Genetics.
[51] J. Rumsfeld,et al. A national clinical quality program for Veterans Affairs catheterization laboratories (from the Veterans Affairs clinical assessment, reporting, and tracking program). , 2014, The American journal of cardiology.
[52] Deepak L. Bhatt,et al. Nonobstructive coronary artery disease and risk of myocardial infarction. , 2014, JAMA.
[53] D. James,et al. The Role of the Niemann-Pick Disease, Type C1 Protein in Adipocyte Insulin Action , 2014, PloS one.
[54] Naomi R. Wray,et al. Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples , 2014, PLoS genetics.
[55] C. Wallace,et al. Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics , 2013, PLoS genetics.
[56] Tanya M. Teslovich,et al. Discovery and refinement of loci associated with lipid levels , 2013, Nature Genetics.
[57] M. Al-Omran,et al. BRCA1 is a novel target to improve endothelial dysfunction and retard atherosclerosis. , 2013, The Journal of thoracic and cardiovascular surgery.
[58] C. Bustamante,et al. RFMix: a discriminative modeling approach for rapid and robust local-ancestry inference. , 2013, American journal of human genetics.
[59] James Brian Byrd,et al. Data quality of an electronic health record tool to support VA cardiac catheterization laboratory quality improvement: the VA Clinical Assessment, Reporting, and Tracking System for Cath Labs (CART) program. , 2013, American heart journal.
[60] J. Danesh,et al. Large-scale association analysis identifies new risk loci for coronary artery disease , 2013 .
[61] Chong Shen,et al. Genome-wide association study in Han Chinese identifies four new susceptibility loci for coronary artery disease , 2012, Nature Genetics.
[62] Stephan Ripke,et al. Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs , 2012, Nature Genetics.
[63] A. Reiner,et al. Genome-Wide Association Analysis of Incident Coronary Heart Disease (CHD) in African Americans: A Short Report , 2011, PLoS genetics.
[64] P. Visscher,et al. Estimating missing heritability for disease from genome-wide association studies. , 2011, American journal of human genetics.
[65] Udo Hoffmann,et al. Genome-Wide Association Analysis Identifies Variants Associated with Nonalcoholic Fatty Liver Disease That Have Distinct Effects on Metabolic Traits , 2011, PLoS genetics.
[66] Mark I. McCarthy,et al. A genome-wide association study in Europeans and South Asians identifies five new loci for coronary artery disease , 2011, Nature Genetics.
[67] Donald W. Bowden,et al. Genome-Wide Association Study of Coronary Heart Disease and Its Risk Factors in 8,090 African Americans: The NHLBI CARe Project , 2011, PLoS genetics.
[68] A. Mannermaa,et al. Transcription factors zeb1, twist and snai1 in breast carcinoma , 2011, BMC Cancer.
[69] Henrik,et al. Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index , 2012 .
[70] Yun Li,et al. METAL: fast and efficient meta-analysis of genomewide association scans , 2010, Bioinform..
[71] Marylyn D. Ritchie,et al. PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene–disease associations , 2010, Bioinform..
[72] Jonathan C. Cohen,et al. A Common Allele on Chromosome 9 Associated with Coronary Heart Disease , 2007, Science.
[73] A. Yashin,et al. Heritability of death from coronary heart disease: a 36‐year follow‐up of 20 966 Swedish twins , 2002, Journal of internal medicine.
[74] A. Ghuran,et al. Cardiovascular complications of recreational drugs , 2001, BMJ : British Medical Journal.
[75] A. Yashin,et al. The Heritability of Mortality Due to Heart Diseases: A Correlated Frailty Model Applied to Danish Twins , 2001, Twin Research.
[76] J. Duffus,et al. Histology , 1931, The Indian Medical Gazette.